In multi-shot high-resolution MRI, the motion of patients often leads to serious degradation of imaging quality. In this study, a novel motion correction method based on deep learning and spatiotemporally encoded MRI was proposed to address this problem. The proposed method is robust to motion without utilizing extra scan or parallel reconstruction. The results of simulation and in vivo rat brain experiments demonstrate its efficacy in reducing image motion artifacts when subject movement exists.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords